Lawrence Economics Blog

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Springing Forward

It is that time of year where the days get longer, aided by a single leap and bound.  This Saturday into Sunday, much of the US will push its clocks forward by one hour.  Despite the “Daylight Savings” moniker, there is no actual daylight saved — it just shifts an hour from the morning to the evening.   The consequences of this likely will affect whether some people live through the rest of March or not, as I pointed out in the New York Times Room for Debate section a few years ago.  My contribution has to do with the changes in pedestrian fatality risks and total fatalities associated with the time change.  I also wrote a more general piece for the Appleton Post-Crescent.  Below is my semi-annual rehash of a previous post…

So, what does a time change look like?  Glad you asked:  The figure from the sunshine authority, Gaisma.com, shows daylight patterns for our own Appleton, Wisconsin.  Each day starts with midnight at the bottom and goes to the top, and the months go left to right.  The blue line is the dawn and the red the dusk.

The Appleton Day
Appleton Time

The switch to DST in March and the switch back to standard time in November are clear — they are the discontinuities (the “breaks”) in the sunrise and sunset curves.  Because we “spring ahead” one hour, the sunrise time on Sunday morning will be one hour later than it was on Saturday.  An early morning walk that was in that daylight on Saturday will be in the dark on Sunday.  To have a sunrise at the same time as Saturday’s, we will have to wait until early April.  The opposite happens in the evening.  Sunset will be one hour later starting on Sunday.  There will be less light in the morning, but more light in the evening.

Light and visibility are extremely important determinants of traffic safety, particularly for pedestrians.  Paul Fischbeck and I looked at data from 1999-2005 on fatalities and travel patterns, and determined that the morning risk increases about 30% per mile walked, while the afternoon risk falls close to 80%.

The figure below shows pedestrian fatality risks from 1999-2005.  The blue and maroon bars show fatality risks per 100 million miles walked in March and April, respectively.  Note that for the 6 a.m. time slot the risks increase about 30%, whereas for the 6 p.m. time slot the risks take a sharp nosedive.  At midday the risks stay right about the same (we found no statistically significant difference in risks for that time period).  Overall, total pedestrian fatalities decrease in the Spring both because risks fall more in the evening than they rise in the morning, and there are many more people out later in the day.

Ped Spring

These data are rather crude in the presentation, as they do not focus specifically on the days leading up to and immediately following the time shifts, which is how researchers typically isolate the effects of the time change.

Here are some references for those interested:

S A Ferguson, D F Preusser, A K Lund, P L Zador, and R G Ulmer “Daylight saving time and motor vehicle crashes: the reduction in pedestrian and vehicle occupant fatalities,” American Journal of Public Health 1995 85:1, 92-95

J M Sullivan and M J Flannagan, “The role of ambient light level in fatal crashes: inferences from daylight saving time transitions,” Accident Analysis & Prevention, 2002 34:4, 487-498

D Coate and S Markowitz, “The effects of daylight and daylight saving time on US pedestrian fatalities and motor vehicle occupant fatalities,” Accident Analysis & Prevention, 2004, 36: 3 351-357

2016-17 Draft Schedule

Click here for the Draft 2016-17 schedule.   There will be some changes to this, but that is effectively what we are looking at for next year.

 

Fall Term 2016 ** DRAFT **
Fall Term 2016 ● ECON 100 (5483) ● INTRODUCTORY MICROECONOMICS (Q) ● (L:40 R:0 W:0) ● 09:50-11:00 MWF ● Jonathan Lhost

Fall Term 2016 ● ECON 245 (5484) ● LAW AND ECONOMICS ● (L:25 R:0 W:0) ● 12:30-02:20 TR ● Jonathan Lhost
Fall Term 2016 ● ECON 300 (5485) ● MICROECONOMIC THEORY (Q) ● 08:30-09:40 MTWF ● Adam Galambos
Fall Term 2016 ● ECON 421 (5486) ● INVESTMENTS ● 09:00-10:50 TR ● Merton D. Finkler
Fall Term 2016 ● ECON 481 (5487) ● ADV ECONOMETRICS & MODELING ● (L:15 R:0 W:0) ● APR ● 01:50-03:00 MWF ● Hillary Caruthers
Winter Term 2017 ** DRAFT **
Winter Term 2017 ● ECON 100 (1482) ● INTRODUCTORY MICROECONOMICS (Q) ● (L:40 R:0 W:0) ● 01:50-03:00 MWF ● Hillary Caruthers
Winter Term 2017 ● ECON 205 (1483) ● INTRO TO INTERNATNL ECONOMICS (G) ● (L:25 R:0 W:0) ● 09:50-11:00 MWF ● Hillary Caruthers
Winter Term 2017 ● ECON 215 (1484) ● COMPARATIVE ECONOMIC SYSTEMS (G) ● 11:10-12:20 MWF ● Adam Galambos
Winter Term 2017 ● ECON 255 (1480) ● START-UP THEATRE ● APR ● 01:50-03:00 MWF ● Staff
Winter Term 2017 ● ECON 380 (1489) ● ECONOMETRICS (Q) ● 09:50-11:00 MTWR ● Jonathan Lhost
Winter Term 2017 ● ECON 380 (1505) ● ECONOMETRICS (Q) ● 03:10-04:20 MTWR ● Jonathan Lhost
Winter Term 2017 ● ECON 450 (1485) ● ECONOMICS OF THE FIRM (Q) ● Arranged● David Gerard
Winter Term 2017 ● ECON 495 (1486) ● TOP: NEW INSTITUTNL ECONOMICS ● Arranged ● David Gerard
Winter Term 2017 ● ECON 601 (1487) ● SENIOR EXPERIENCE: READING OPT ● 12:30-02:20 T ● Adam Galambos
Winter Term 2017 ● ECON 602 (1488) ● SENIOR EXPERIENCE: PAPER ● APR ● Arranged ● Jonathan Lhost
Spring Term 2017 ** DRAFT **
Spring Term 2017 ● ECON 100 (3520) ● INTRODUCTORY MICROECONOMICS (Q) ● (L:40 R:0 W:0) ● 08:30-09:40 MTWR ● David Gerard
Spring Term 2017 ● ECON 225 (3521) ● DECISION THEORY ● 11:10-12:20 MWF ● Adam Galambos
Spring Term 2017 ● ECON 280 (3522) ● ENVIRONMENTAL ECONOMICS ● (L:25 R:0 W:0) ● 12:30-02:20 TR ● David Gerard
Spring Term 2017 ● ECON 320 (3525) ● MACROECONOMIC THEORY (Q) ● 09:50-11:00 MTWR ● Hillary Caruthers
Spring Term 2017 ● ECON 320 (3542) ● MACROECONOMIC THEORY (Q) ● 03:10-04:20 MTWR ● Hillary Caruthers
Spring Term 2017 ● ECON 400 (3523) ● INDUSTRIAL ORGANIZATION (Q) ● (L:15 R:0 W:0) ● 11:10-12:20 MWF ● Jonathan Lhost
Spring Term 2017 ● ECON 405 (3524) ● INNOVATION & ENTREPRENEURSHIP ● 08:30-09:40 MWF ● Adam Galambos
Spring Term 2017 ● ECON 415 ● INDIVIDUALITY & COMMUNITY ● (L:18 R:0 W:0) ● 12:30-02:20 TR ● Steven Wulf

Click here for course descriptions.

The Evangelical (and Wisconsonian) Roots of American Economics

Bradley W. Bateman, President of Randolph College, Keynesian scholar, and frequent visitor to Lawrence, has a piece up at The Atlantic Monthly today on the surprising religious past of American economics.

A big part of the story is the leadership of Richard T. Ely, an extremely controversial figure who spent more than thirty years of his career at the University of Wisconsin directing the School of Economics, Political Science, and History.

Of course, the religious roots were not long-lived, as President Bateman notes:

It is, of course, hard to recognize this earlier type of economist in today’s profession. Like the university, the discipline of economics was secularized after 1920. Around this time, the discipline of philosophy came to be dominated by logical positivism—essentially, the idea that the scientific method is the only way to arrive at true, factual knowledge—and this school of thought greatly influenced American economists as the landscape of their own discipline was changing. They developed the idea that their new analytical focus was value-free—a premise still taught in most introductory economic textbooks.

But, of course, is not, which is important to recognize.

Bateman doesn’t really comment on whether the Wisconsonian influence has been diminished.  You can find The Atlantic piece here.

For more thorough treatment, check out (then) Professor Bateman in the Journal of Economic Perspectives.

An easy subject at which very few excel!

The study of economics does not seem to require any specialised gifts of an unusually high order. Is it not, intellectually regarded, a very easy subject compared with the higher branches of philosophy and pure science? Yet good, or even competent, economists are the rarest of birds. An easy subject, at which very few excel!  — John Maynard Keynes

I came across this gem at Brad Delong’s website, where he is having a dialog with Paul Krugman about the use of graphs in Econ 101, and specifically whether Production Possibilities and Edgeworth Boxes should be introduced at the introductory level.

This is certainly a conversation we are having on our floor.  I think we generally introduce PPFs, but not the Edgeworth Boxes in our introductory courses, and our Econ 300 students get the Ysidro Edgeworth treatment.  I guess I’m all ears if you have thoughts on the topic.

As for the more obnoxious point that economics is a seemingly lightweight subject that few are good at, huh.  Keynes continues:

The paradox finds its explanation, perhaps, in that the master-economist must possess a rare combination of gifts. He must reach a high standard in several different directions and must combine talents not often found together. He must be mathematician, historian, statesman, philosopher-in some degree. He must understand symbols and speak in words. He must contemplate the particular in terms of the general, and touch abstract and concrete in the same flight of thought. He must study the present in the light of the past for the purposes of the future.

That’s from his obituary for Alfred Marshall, author of the incredible Principles of Economics, the profession’s first textbook, and namesake of Marshallian Demand!  Truly a pioneer and an intellectual giant, regardless of what Keynes says here.

It’s nice to see someone say something nice about economists, even it if is an economist, and even if it was 90 years ago.

 

 

 

A Slippery (North?) Slope

In the past, I’ve often harangued my environmental economics students with the question of why, if we are running out of natural resources, the futures markets don’t project substantial increases in oil prices.  After all, a constrained supply should lead to higher prices on the one hand, and the industrialization of China, India, and other countries suggests that world demand will continue to increase (or, at least, it won’t decline substantially).   Add together lower supply and higher demand and we should be seeing higher prices.

The scholars at www.Env-Econ.net have a nice overview of the canonical Hotelling Rule that provides some logic for increasing oil prices, along with a potential price trajectory based on marginal production costs.

Yet, anyone looking out in the world today certainly has noticed that oil prices have dropped precipitously.  This screen grab from Bloomberg shows that in late 2014 oil prices moved from the $80-100 range to the $40-$60 range for the better part of 2015.  Prices have continued to slide, and were just north of $30 as of a few minutes ago.

Bloomberg Markets

So what are we to make of all of this? Continue reading A Slippery (North?) Slope

Is American Economic Growth in a Gordonian Knot?

One of the reasons, I suppose, that there has never been a more interesting time to be an economist is that we can all see remarkable technological advances unfolding in front of us, but no one quite agrees what to make of them.  A few years ago, Tyler Cowen published a little e-book, The Great Stagnation, that was widely talked about and reviewed in about a million places.  The man-bites-dog angle there was these technological changes have not translated into more robust growth (building on the Solow Paradox, I suppose, that we “can see the computer age everywhere but in the productivity statistics.”)

Since then, we have seen MIT’s techno-optimist Eric Brynjolfsson weigh in with The Race Against the Machine and Northwestern’s Robert Gordon counter with his “headwinds” argument.  Specifically, Gordon argues that our most productive days are behind us, and that innovation will be insufficient to enable us to sustain the 2% per capita real growth of the 20th century.  If you are so inclined, you can watch Brynjolfsson and Gordon square off in this TED debate.

Gordon has now substantially bolstered his argument with a new book, The Rise and Fall of American Growth.  The massive 762-page tome will certainly be the hottest economics book since Thomas Piketty published Capital in 2014 (and probably read cover-to-cover by approximately the same percentage of readers). But if you don’t have time to wade through the text, there are plenty of people discussing it, including Gordon himself in this PBS News Hour video.

A number of big hitters have offered their thoughts, including Paul Krugman in the New York Times, LU Econ Blog favorite, Ed Glaeser in the Wall Street Journal, and the aforementioned Tyler Cowen for Foreign Affairs.  I expect to see many, many more in the coming weeks.

Certainly, there are plenty of resources to get you thinking about the topic even if you don’t have the book itself.  I currently have procured the Mudd’s copy, and will report back my thoughts when I get to it in 2018.

 

 

“There has never been a more interesting time to be an economist, I think”

Quora is a website dedicated to “sharing and growing the world’s knowledge.”  Ask a question, and the good folks at Quora will find someone with first-hand knowledge to answer it.

Today’s contribution to sharing and growing is “Why do technology companies hire economists?”

My response, of course, is Who wouldn’t want to hire an economist?. This response was unsatisfying enough that Quora asked Susan Athey, Professor in the Economics of Technology at Stanford’s Graduate School of Business, to address the question. Here is my condensed version of her response.

This is a great time for economists in tech companies—the most interesting firms in Silicon Valley are hiring chief economists as well as economic teams at a very rapid clip….

Each tech company, and each chief economist, is different, but there are several main categories.  First are microeconomic issues involved in pricing and product design…  Second is corporate strategy…  Third is public policy… Fourth, and closely related, are direct legal and regulatory challenges — antitrust/competition policy issues and regulatory investigations.

More junior economists have a wide variety of roles in tech firms.  They can take traditional data science roles, be product managers, work in corporate strategy, or on policy teams.  They would typically do a lot of empirical work.

My emphasis (see also, here).

I was particularly interested in this nugget about why economists might be particularly valuable in a room full of data:

I have found that economists bring some unique skills to the table.  First of all, machine learning or traditional data scientists often don’t have a lot of expertise in using observational data or designing experiments to answer business questions.  Did an advertising campaign work?  What would have happened if we hadn’t released the low end version of a product?  Should we change the auction design?  Machine learning is better at prediction, but less at analyzing “counter-factuals,” or what-if questions.  (I’m currently doing a lot of research on modifying machine learning methods to make them more suitable for causal inference).

Click through for her complete answer to the original question, along with her insights on Bitcoin, the impacts of machine learning on economic science, the potential benefits of collusion, and some elaboration on her contention that “there has never been a more interesting time to be an economist.”

 

The Continuing Debate on Immigration & Wages

I was surprised and pleased at the level of interest and quality of discussion surrounding U.S. immigration policy in my public economics course last term. I was reminded of this when I saw one of the most prominent scholars in this area, George Borjas, has revived his LaborEcon blog.

Borjas is noted for, among other things, his work on the wage effects of the Mariel boatlift, when Fidel Castro sent thousands of unskilled Cuban immigrants to the shores of Miami in 1980.  In September, he circulated a National Bureau of Economics Research Working paper, “The Wage Impact of the Marielitos: A Reappraisal,” that he describes thusly:

At least in my corner of the universe, it created a disturbance in the force reminiscent of the destruction of Alderaan…

There are a couple of excellent summaries of what is going on, including David Frum’s “The Great Immigration Data Debate,” and Noah Smith’s more provocatively titled “An Immigrant Won’t Steal Your Raise.” Here is a summary of Smith’s summary:

The most important and widely cited such study is a 1990 paper by economist David Card… Standard Econ 101 theory says that a big increase in labor supply should reduce wages for local workers,… [b]ut Card found something startling: the negative impact on native Miamians was negligible. Neither wages nor employment fell by a measurable amount…

But in 2015, George Borjas of Harvard University’s Kennedy School came out with a shocking claim — the celebrated Card result, he declared, was completely wrong…

Now, in relatively short order, Borjas’ startling claim has been effectively debunked…

Borjas responded quickly and forcefully with the equally provocatively titled “Lies, Damned Lies, and Immigration Statistics.”

This is certainly a spirited debate, and given the topic’s import for the 2016 elections, one worth paying attention to.

Turn and face the strange

Are economists ideological zealots who come up with models and quantitative devices to corroborate their preconceived notions?  That may be the case for some, but Adam Ozimek at Moody’s Analytics catalogs a number of cases where prominent economists have changed their opinions based on empirical work in the field.

Narayana Kocherlakota spent three years at the head of the Minneapolis Fed criticizing monetary policy as risking out-of-control inflation and unlikely to help the economy. Then in 2012, he made an about face, telling the New York Times that “a wave of research gradually convinced him that he was wrong.” As a result he became one of the most strident proponents of more monetary stimulus.

Ozimek cites economists who have changed their minds on other matters, including that free trade can lead to job losses in some areas that are both substantial and persistent, that recessions can have permanent negative effects on output, and that standardized tests may well be a good measure of teacher performance.

Definitely worth thinking about his parting shot: “Has a single economics study changed your mind on an important issue?”

 

UPDATE:!!!  Tyler Cowen weighs in with a long list.   And Paul Krugman, too!

I’m Sinking in the Quicksand of my Thoughts

The winter 2016 issue of Resources Magazine is out, featuring some germane pieces for my courses on the “real” costs and benefits of federal regulations, and the Impacts of Biofuel Mandates on Food Prices and the Emissions.

The first piece is an interview with Richard Morgenstern on his news study where he retrospectively evaluates the costs and benefits of regulations.  Clearly, Morgenstern has been interested in this area for some time, having published “On the Accuracy of Regulatory Cost Estimates” in the Journal of Policy Analysis  and Management back in 2000, a stalwart in the ECON 444 course.   One of the main takeaways is that this exercise is something that is not regularly done and is surprisingly hard to complete.  The forthcoming study Morgenstern talks about evaluates nine policies.

The second piece, as the title suggests, tries to isolate the impact of biofuel mandates on food prices.  The US Environmental Protection Agency has a Renewable Fuel Standard (RFS) that requires a certain portion of vehicle fuel to contain “renewable” sources.   In practice, this generally means corn ethanol, and as a result the demand for corn is much higher than it would otherwise be (more than 40 percent of US corn is used to produce ethanol).

This is chock full of partial-equilibrium analysis.  The increase in the demand for corn should lead to a movement along the supply curve, and a simultaneous decrease in the supply of other substitutes in production.   Meanwhile, as world income has gone up and many in developing countries are eating diets more dependent on animal protein.   This further increases the demand for cereals for animal feed (for reasons I will let you infer).

Ujjayant Chakravorty has developed a global land use model that isolates the effect of the RFS on food prices and emissions.  Here are the key findings:

[I]f there were no biofuel mandates, food prices would increase—by about 15 percent in 2022 compared to the base year 2007.  When we superimpose the US and EU biofuel mandates, world food prices go up by 32 percent.

Our results highlight the impact of increased meat and dairy consumption on the projected growth of food prices. Put another way, if diets were kept constant, food prices would actually fall over time without energy regulation. Then, with the biofuel mandates, they would rise by only 7 percent in year 2022.

Ironically, the RFS doesn’t do much for global carbon emissions.  Follow this logic:

An important conclusion from our analysis is that under no scenario do we get a major reduction in global carbon emissions. Under the RFS, US emissions fall by about 1 percent; however, that leads to a lowering of global crude oil prices and an increase in oil consumption overseas. Moreover, because of all the new land being farmed, the RFS also causes an increase in carbon emissions. Aggregate global carbon emissions (from both direct burning of fuels and land use changes) increase from 13.4 billion tons of carbon dioxide equivalent to 17.8 billion tons in 2022.

Emphasis mine in both cases.

As a colleague of mine used to say, if you want to grow fuel, grow fuel.  Don’t grow corn and turn it into fuel.

If the topic interests you, check out the symposium on agriculture in the Winter 2014 Journal of Economic Perspectives.

Economics is What Economists Do

The post title is, of course, from the late, great Jacob Viner, who tells us that it isn’t totally easy to characterize exactly what it is that we economists do.  The alive, possibly great Daniel Hamermesh from the University of Texas has been making some headway on cataloging exactly what that is.  And, increasingly, it appears that the top journals are featuring more empirical work and less theory.

Justin Fox at Bloomberg tells us all about it.*

Or just look at the picture:

Is this part of the big data revolution we’ve been hearing so much about?

Potentially more interesting is that experimental makes up almost 10% of the total.

 

* Actually, Hamermesh published the paper several years ago, but I guess the news cycle is slow getting around to reading the Journal of Economic Literature.

We did a Similar Post Last Year

The 2015 edition of the eponymous Which Famous Economist are you Similar to? interactive tool is now available, and once again — though once again I probably shouldn’t be telling you this — yours truly has been paired with Daren Acemolgu.  (Acemoglu, as you possibly know, is the MIT superstar economist who is the subject of the Daren Acemoglu Facts tumblr page, chock full of economist “humor”).

As far as the Which Famous Economist site goes, the data are from the University of Chicago’s IGM Economic Experts Panel, which periodically surveys many economists on issues of the day.  The matching is done via principal components, which is somewhat ironic, given principal-component modeling isn’t really part of the economist’s standard canon of quantitative tools.

If you decide to take the poll, I recommend that you leave the questions you haven’t thought about (or don’t know anything about) blank.  The authors say that “accuracy” requires at least 20 responses out of the 30 questions.

Which famous economist are you most similar to

I’m the red dot, and the arrow points to Professor Acemoglu.  Robert Hall and José Scheinkman are the dots closest to mine, and you can read the explanation for why I was not paired with one of them in the figure’s legend.

The site also allows you to highlight where your views differ from the consensus view (I have a higher opinion of my peers’ knowledge of book prices, for example.)  It also contains a correlation matrix for each economist in the survey pool — all are positively correlated!

See you next year.

 

 

Ta-Nehisi Coates Convocation Thursday

We are fortunate to have on campus one of America’s rising public intellectuals, Ta-Nehisi Coates, to deliver the Convocation on Thursday.  His talk is “Race in America: A Deeper Black,” starts at 11:10 in the Lawrence Memorial Chapel.

Mr. Coates is a recipient of one of this year’s Macarthur “Genius” Awards,  and his recent book, Between the World and Me, is a finalist for the National Book Award in non-fiction.

I became familiar with Coates from his writing in The Atlantic, where last year he wrote “The Case for Reparations,” where he argues that African Americans should be compensated for the past abuses of slavery, Jim Crow, “separate-but-equal,” and continuing racist housing policies.    A more recent piece, “The Black Family in the Age of Mass Incarceration” explores the devastation that a confluence of racist housing policies, drug laws, and differential policing has had on black families and communities.   The tragic thesis that Coates forwards is that the mass incarceration of African-American men is mostly by design, and not some unintended consequence of ill-conceived public policies.

The Convo is at 11:10.   I suggest you get there early if you want a seat.

Innovation in Everything

What distinguishes the ‘scientific’ economist from all the other people who think, talk, and write about economic topics is a command of techniques that we class under three heads: history, statistics, and ‘theory.’ The three together make up what we call Economic Analysis.

That’s Joseph Schumpeter in Chapter 2 of his famous History of Economic Analysis. He believed that economics programs should emphasize and connect all three of those approaches. Those of us in ECON 405, The Economics of Innovation and Entrepreneurship, have been working to do just that, or at least the history and theory bit. To take a break from immersing themselves in the history of innovation and mathematical models of innovation and entrepreneurship, students have been exploring innovation in a variety of fields, and recording their journeys weekly on a blog. So, you can also learn about theatrical innovation, microfinance in Pakistan, the habits of the poor, private equity and innovation, innovation in the construction industry, multisided markets, telematics, or big data and consumer goods. Enjoy!

************ Advice for Potential Majors & AIM Placement

Here is our message to those of you thinking about pursuing an economics major (or minor).  For more on the collegiate economics major more generally, here is some information from the American Economics Association.

Advice to Potential Majors:  Students interested in a major in Economics should begin with introductory classes in economics and mathematics.  The first economics class is ECON 100.

Students who have satisfied the ECON 100 requirement should consider taking 200-level classes based on their own interests (e.g., 200 Development Economics, 205 International Economics, 225 Decision Theory, 245 Law & Economics, 280 Environmental Economics, 290 Economics of Medical Care).

There are three intermediate theory courses that are offered sequentially each year – ECON 300 Microeconomics in the fall, ECON 380 Econometrics in the winter, ECON 320 in the spring.  These courses are most effective when taken sequentially in either the sophomore or junior year.  Freshman should not enroll in these courses.

Sophomore year is a good time to take ECON 225 Decision Theory.   This is not a required course, but we strongly recommend it for all majors and minors.

Mathematics Requirements and Advice:  The introductory mathematics courses are essential because they are foundational to intermediate theory courses.  Calculus (MATH 120 and 130 or MATH 140) is a prerequisite for ECON 300 and ECON 320.  Statistics (MATH 107 or the equivalent) is a prerequisite for ECON 380.

For the purposes of the Economics Department, we believe students should consider MATH 120 and 130 if they are interested in applied problem solving and developing some Excel skills.   Students who plan to take math beyond the calculus sequence should take MATH 140.   The decision on which calculus to take is probably worth a discussion both with the math and the econ department faculty.

A typical sequence for a student who comes in as an economics major.

Freshman: Introductory Economics (ECON 100), 200-level courses based on student interest, Calculus (MATH 120 and 130 or MATH 140).

Sophomore:  Intermediate sequence (ECON 300, 380, 320), 200-level courses based on student interest, Statistics (MATH 107).  ECON 300 and MATH 107 are offered in the fall.

Junior-Senior: Advanced electives.

This sequence can be pushed back a year for those who decide during their sophomore year to pursue an economics degree.

MINOR: The minor requirements are indeed minor.  No significant planning is necessary during the Freshman year to complete this degree, though our recommendations in terms of taking introductory economics and mathematics courses remain the same for majors and minors alike.

 

AIM Placement: If you scored a 4 or 5 on the AP micro test, you can obtain credit through the Registrar’s office for ECON 100.  This satisfies that requirement for the department, though we strongly suggest you take at least one 200-level course before beginning the 300 sequence.  Talk to a faculty member in economics for appropriate recommendations.

If you earned a 4 or a 5 on the AP macro test, you can obtain 6 units of Lawrence credit, and you should take Economics 100.

GDP: Useful Construct or Weapon of Mass Misdirection

Estimates of GDP growth vary widely (often well over 1 percentage point) from the initial one (typically at the end of the first month after the quarter) to a final one (up to a year later).  This post addresses such variation and the debate about whether it arises from measurement error or definitions based on contemporary politics.  No matter which view you might hold, it’s pretty clear that macroeconomic policy should not be based on early estimates of quarterly GDP growth.

Last month, the Bureau of Economics Analysis (BEA) reported that 2nd Quarter 2015 GDP had increased by 3.7% (in annualized terms.)  Its first estimate (in July) was 2.3%.  For the first quarter of 2015, we now have three estimates: earliest +0.2%, 2nd -0.7%,  and most recent (August) +0.6%. In short, we can’t easily tell whether the economy grew or not.

Some of you may recall that GDP can be calculated in three ways:  1) the sum of what it would cost to purchase all goods produced in the US for final sale, 2) the income paid to all factors of production in the U.S. plus depreciation and indirect business taxes, and 3) the sum of all values added.

Typically no one calculates the third but recently, the BEA has begun to provide the income-based measure.  For the first quarter of 2015, the second estimate was 0.4% after an initial estimate of 0.1%.  For the second quarter of 2015, the only estimate of growth of gross domestic income was 0.6% (well short of the 3.7% GDP growth estimate cited above.)

GDP ResidualThe difference between income based and expenditure based methods, as reflected by the residual (in red) in the above chart, is far from trivial. The blue line reflects gaps in converting nominal GDP to real GDP.  These were substantial in the past, but appear not to be a problem today. See the St. Louis Federal Reserve’s discussion of this residual for details.

In a recent article entitled “Weapons of Economic Misdirection,” John Mauldin traces the history of GDP accounting and asks whether the changes reflect improved knowledge of the economy – such as updates to inventory, export, and import data – or political manipulation.  Keynes and Hayek disagreed about what to measure and how it should be used, and Simon Kuznets, who created the national income accounts and received one of the first Nobel prizes in economics for his work, disagreed with the Commerce Department regarding the same two concerns.

Mauldin refers to and quotes from Diane Coyle’s new book GDP: A Brief But Affectionate History to illuminate the controversy.  I encourage you to read Mauldin’s posting.

I’ll give Chinese Premier Li Keqiang the last word (especially with reference to the accuracy of Chinese GDP estimates – which seem to matter to many investors in the U.S.) “Chinese economic statistics are ‘man made’ and, apart from the numbers for electricity use, bank lending and rail freight, are for reference only.”  Gives you great confidence, doesn’t it?

 

 

What Can I do with an Economics Major?

Why not take him/her out to lunch with you?

No, no, no.  Of course, I’m talking about what sort of Life After Lawrence is out there for our economics majors?  Well, the American Economic Association is encouraging its members to share this video.  Here’s the link:

A career in Economics… it’s much more than you think

Much more than finance, banking, business and government, a degree in economics is useful to all individuals and can lead to many interesting career choices. These four diverse individuals offer their insights on how a background in economics can be a tool for solving very human problems.

  • Marcella Alsan, a physician of infectious disease, discusses why she needed to pursue a degree in economics to improve the lives of her patients.
  • Randall Lewis, a research scientist at Google, uses economics and “big data” as tools to improve the functioning of markets.
  • Britni Wilcher, a PhD student of economics, offers insight on some misconceptions about economists and factors influencing her career path decision.
  • Peter Henry, dean at the NYU Stern School of Business, points to the true nature of economics and the importance of diverse voices informing the field.

Here is the American Economic Association’s link of information for students considering an economics major, covering topics from what economists do to what type of skills you will develop as an economics major.

If you are considering a major, please click on the Advice for Potential Majors link that you should see in your left frame.